A question of justice: Critically researching suicide with Indigenous studies of affect, biosociality, and land-based relations
Bibliographic record
Abstract
This paper considers how Indigenous studies can inform the evolution of critical research on suicide. Aligned with critiques of mainstream suicidology, these methodological approaches provide a roadmap for structural analysis of complex systems and logics in which the phenomenon of suicide emerges. Moving beyond mere naming of social determinants of suicide and consistent with calls for a theory of justice within suicide research, Indigenous studies helps to advance conceptual knowledge of suicide in descriptive means and enhance ethical responses to suicide beyond psychocentric domains. Through centering Indigenous theories of affect, biosociality, and land-based relations, this article examines what new knowledge of suicide can emerge, as well as what ethical responses are possible to suicide and to a world where suicide exists. This new knowledge can inform practices for critical suicide studies which are invested in resisting structural violence, nourish agency, dignity and freedom for those living and dying in often-unlivable presents, and enhancing livability for individuals, communities, and the environment living under shadows of empire. Implications for theory, ethics, and suicide research and prevention practice are considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.054 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.121 |
| Scholarly communication | 0.010 | 0.019 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".